Method for detecting fire with light section image to sense smoke

ABSTRACT

The present invention relates to a method for detecting fire with light section image to sense smoke. Infrared radiation arrays ( 1 ) and infrared cameras ( 2 ) are provided in a monitored area. The images of the infrared light spots transmitted by the infrared radiation arrays ( 1 ) are converted into video signals by the infrared cameras ( 2 ), and transferred to a video switcher ( 3 ). The video switcher sends the video signals received from the infrared cameras to a computer ( 4 ) one by one. The computer processes the signals. If fire is sensed, the computer controls the alarm unit ( 5 ) to alarm by a linkage.

FIELD OF THE INVENTION

The present invention relates to a method for detecting fire, inparticular to detect fire with light section image to sense smoke.

DESCRIPTION OF THE RELATED ART

In most cases, the presence of smoke in fire is earlier than that ofopen fire, so a smoke-sensing fire detector has been applied widely. Atpresent, the smoke-sensing fire detectors used in various places includeionic smoke-sensing fire detectors, photoelectric smoke-sensing firedetectors, as well as the analog alarm type fire detectors and automaticfloating type fire detectors responding to a threshold, which have theprimary intelligence. The existing fire detectors may alarm in error orlate due to the color of the smoke, the size of the particles, theheight of the space, airflow, and shake, etc., and alarm in error ormiss the alarm due to the dust accumulation and the environmentalvariation.

OBJECT OF THE INVENTION

Accordingly, it is an object of the present invention to provide amethod for detecting fire with a smoke-sensing light section image toachieve a high sensitivity to flaming fire and non-flaming fire, highanti-interference ability, low error alarm ratio, and adaptation to thelarge space.

SUMMARY OF THE INVENTION

The method of the present invention is implemented as follows.

According to one aspect of the present invention, there is provided amethod for detecting fire with a smoke-sensing light section image,characterized in that infrared radiation arrays and infrared cameras areprovided in a monitored area, the infrared light beams emitted by theinfrared radiation array pass through the monitored area, and theinfrared light spots are imaged on the light target arrays of theinfrared cameras, the images of the infrared light spots are convertedinto video signals by the infrared cameras, and then transferred to avideo switcher, the video switcher sends the video signals received fromthe infrared cameras to a computer one by one in polling manner, andwherein after the video signals are input to a computer, the computeranalyzes and processes the variation of the video signals in the mannerof template matching, tendency analysis and correlation analysis, thecomputer controls an alarm unit to alarm by a linkage if fire is sensed.

COMPARISON WITH PRIOR ART

The advantages of the present invention are in that:

(1) The light section formed by multi-beam light can cover the protectedspace in arbitrary curved surface, so that the area of the fast responseregion is greatly increased, and then it is possible to alarm in a largespace early.

(2) Correlation analysis for adjacent beams in the light section caneliminate the error alarm caused by accidental factors in a single-beamof light fire alarm unit.

(3) The shift of operating conditions caused by dust accumulation isdetected and traced automatically. When the shift exceeds a given range,a faulty signal is produced automatically. Meanwhile, such a firedetector can automatically modify the operating parameters thereof inaccordance with the variation of the environment, so that the error andmissed alarm caused by the dust accumulation and the environmentalvariation are reduced significantly.

(4) Surface imaging auto-tracing fixed-point detection may completelysolve the problems of the error alarm caused by installing and movingthe conventional linear smoke-sensing unit.

(5) By using the technique of surface imaging, the method for sensingsmoke with light section image is capable of distinguishing an emittinglight source from an interference light source. Therefore, theanti-interference performance of the system is enhanced, and then theapplication fields are enlarged widely.

The method of the present invention may be applied to the fire detectionin a large and long space. It can achieve the abilities to adapt variousenvironments, to acquire information with low cost, to install facilely,and to install in multi-layers.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other objects, advantages, and features of the presentinvention will be more apparent from the following description taken inconjunction with the accompanying drawings, in which:

FIG. 1 is a schematic block diagram showing a fire detection system ofan embodiment of the present invention;

FIG. 2 is a graph showing the relationship of smoke density versustransmission intensity of light; and

FIG. 3 is a flowchart explaining the steps preformed when the firedetection system shown in FIG. 1 detects fire.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

Referring to FIG. 1, the fire detector of an embodiment of the presentinvention is described. As shown in FIG. 1, the fire detection systemincludes infrared radiation arrays 1, infrared cameras 2, a videoswitcher 3, a computer 4, and an alarm unit 5 which is controlled by alinkage. Reference numeral 6 shows the principle of forming a lightsection. Infrared radiation arrays 1 and infrared cameras 2 are providedin the monitored space. According to the requirements of fire preventionfor the site, the infrared radiation arrays 1 and the infrared cameras 2are arranged in such a way that the section formed by the infraredradiation arrays and the infrared cameras may show the conditions of theall space of the site to monitor on the monitored space effectively. Theinfrared light beams emitted by the infrared radiation arrays passthrough the monitored space, and the infrared light spots are imaged onthe light target array of the infrared cameras. The infrared cameras setat different positions can convert the image of infrared light spotsinto video signals and then transfer them to a video switcher 3. Thevideo switcher 3 sends the video signals to the computer 4 one by one inpolling manner. The computer 4 analyzes, on the basis of the strength ofthe received video signals, whether there is fire or not. If fire issensed, the computer 4 may control alarm unit 5 to alarm by a linkage.

FIG. 2 is a graph showing the relationship of smoke density versustransmission intensity of light and FIG. 3 is a flowchart explaining thesteps preformed when the fire detection system shown in FIG. 1 detectsfire. Light beams may be refracted, scattered and absorbed when theypass through the air. After the beams pass through the air, theirintensity directly depends on the density of particles that may refract,scatter and absorb the light in air. The relationship between them is asfollows:

 I _(λ) =I _(λ0)exp(−KL)

where I_(λ0) indicates the intensity of the incident light, I_(λ)indicates the intensity of the light which passes through the smoke, Lis the average run length of the ray and K is the extinctioncoefficient, which is an important parameter to characterize extinctioncoefficient, and may be further expressed as the product of theextinction coefficient(K_(m)) of the smoke mass density per unitmultiplied by the smoke mass density (M_(s)).

K=K _(m) M _(s)

where K_(m) is extinction coefficient, which is dependent on the sizedistribution of smoke particles and properties of the incident light,that is,$K_{m} = {\frac{3}{2\quad \rho_{s}}{\int_{d_{\min}}^{d_{\max}}{{\frac{1}{d} \cdot \frac{\delta \quad M_{s}}{\delta \quad d}}{Q_{est}\left( {\frac{d}{\lambda}n_{r}} \right)}\delta \quad }}}$

where δ is differential symbol, d is the diameter of smoke particles,ρ_(s) is the density of smoke particles. Q_(ext) is the extinctioncoefficient of a single particle, which is a function of a ratio of theparticle diameter to the wavelength (d/λ) as well as compoundrefractivity of particles (n_(r)). As common wood or plastic is burned,the value of smoking extinction coefficient K_(m) is about 7.6 m²/g. Thevalue of smoking extinction coefficient K_(m) thereof in pyrogenicdecomposition is about 4.4 m²/g.

When wood or plastic is under the condition of the initial fire,K=4.4M_(s). If detecting distance L is 50 m, then

I _(λ) =I _(λ0)exp(−220M _(s))

Accordingly, the fire can be judged by analyzing the variations of I_(λ)after I_(λ0) and M_(s) have been known. In the actual operation, sincethe infrared light beams pass through the air and form the images ofinfrared light spots on infrared cameras with the spot brightness X,where X_(∝)I_(λ)), one can determine whether the fire appears or not byanalyzing the attenuation of X.

Each of the infrared cameras faces a string of infrared light spots.These infrared light spots are sent to a computer by a video switcherone by one in polling manner. These spots are digitized by the computerand then are stored in the memory of the computer. Firstly, it isnecessary to segment and extract these light spots in order to measuretheir brightness. The light spot is separated from its background bymeans of dynamic histogram threshold segmentation and template matching,so that a series of brightness values of the light spots are measured inreal time.

X ₁(1)X ₂(1)X ₃(1) . . . X _(n)(1)

X ₁(2)X ₂(2)X ₃(2) . . . X _(n)(2)

X ₁(3)X ₂(3)X ₃(3) . . . X _(n)(3)

X ₁(t)X ₂(t)X ₃(t) . . . X _(n)(t)

where t is the measured value at timing t, n is the n−th spot.

According to the present invention, it can determine whether there isfire or not by using the fire recognition mode via analyzing x₁(j) (i=1,2 . . . , j=1, 2 . . . t). The present invention utilizes firerecognition modes of mode recognition, sustained tendency and predictionadaptation. Its operating principle is as follows.

Image information is analyzed in real time, and the information iscompared and matched with smoke features, and then conclusions can beobtained.

For one specific light spot, a progression is extracted from acontinuous timing diagram,

x _(i) ={x _(i)(k) |k=1, 2, . . . , n}

x ₀ ={x ₀(k) |k=1, 2, . . . , n}. . . reference progression

The noise of each of the progressions is removed by analyzing thewavelet, and the progressions are classified approximately. Themechanism of the processing is in that the singularity of the signalwhich is based on features of white noise is completely different underwavelet transform. Now, it is analyzed as follows:

f(x)ε° C.(R) (0<a<1) if

|f(x)−f(y) |=0 (|x−y| ²)

it is assumed that ψ(x) is a allowable wavelet, and |ψ(x)|, |ψ′(x) |=0(1+|x|⁻²), it is written as

ψ_(j,k)(x)=2^(½)ψ(2′x−k)

W _(2′) f(x)=2^(½)∫_(R) f(t)ψ(2′t−x)dt

then

|W ^(j) _(2′) f(x) |=O(2^(−(½+α)j))

For a wide stationary white noise n(x) with α² variance, it can concludeW2^(j)n(x)=2^(j)/2(n(t) ψ(2^(j)t−x)), and ψ(x) is supposed as a realfunction. Thus

|W2′n(x)²=2′∫∫_(R) n(u) n(v) ψ(2′(n−x)) ψ(2′(v−x))dudv

then

E|W2′n(x) |²=2′∫∫_(R)σδ(u−v) ψ(2′(u−x)) ψ(2′(v−x))dudv =2′σ²∫|(2′(u−x))|² du =σ ²∥ψ∥²

It indicates that W2^(j)n(x), which is an average power of a stationaryrandom process, has no relation with the size of 2j. Then, each of theprogression calculates the tendency values with the variable windowsustained time tendency algorithm. The procedure is as follows: definingan accumulative function K(n) as${K\left( {n + 1} \right)} = \left\{ \begin{matrix}{{k\left( {(n) + 1} \right)}{u\left( {{y(n)} - {St}} \right)}} & {{St} > 0} \\{{k\left( {(n) + 1} \right)}{u\left( {{St} - {y(n)}} \right)}} & {{St} < 0}\end{matrix} \right.$

St is the alarm threshold. U(·) is a unit step function$\left. {{y(n)} = {{\sum\limits_{i = 0}^{N + {k{({n - 1})}} - {2N} + {K{({n - 1})}} - 1}\quad \left. {\sum\limits_{j = 1}{{sign2}\left\lbrack {{sign1}{\left( {{x_{0}\left( {n - i} \right)} -} \right.}{x_{0}\left( {n - j} \right)}} \right.}} \right)} + {{sign1}\left( {{x_{0}\left( {n - j} \right)} - {RW}} \right)}}} \right\rbrack$

where N is the length of a window. A short window is used in normaldetection. After the tendency value has exceeded the alarm threshold,K(n) will increase gradually. Sign2 and sign1 are sign functions.${{sign1}(x)} = \left\{ {{\begin{matrix}1 & {x > s} \\0 & {{- s} \leq x \leq s} \\{- 1} & {x < {- s}}\end{matrix}{{sign2}(x)}} = \left\{ \begin{matrix}1 & {x > 1} \\0 & {{- 1} \leq x \leq 1} \\{- 1} & {x < {- 1}}\end{matrix} \right.} \right.$

S is a turning threshold. The relative tendency value is defined as

τ(n)=y(n)/(N*(N−1))

when τ(n)ε[r1, r2], the associated matching conditions of each of theprogression will be determined. If the associated values exceed theassociated predetermined value in their entirety, then it can beconfirmed that fire is present.

The associated coefficient is defined as${\zeta_{l}(k)} = \frac{{{Min}_{l}{Min}_{k}{\Delta_{l}(k)}} + {\rho \quad {Max}_{l}{Max}_{k}{\Delta_{l}(k)}}}{{\Delta_{l}(k)} + {\rho \quad {Max}_{l}{Max}_{k}{\Delta_{l}(k)}}}$

Where Δi(k)=|x₀(k)−x₁(k)| is referred to as the absolute differencebetween the k-th index x₀ and x₁, ρε(0, +∞) is referred to asdistinguishing coefficient, Min_(l)Min_(k)Δ_(l)(k) is referred to as atwo-level minimum difference, Max_(l)Max_(k)Δ_(l)(k) is referred to as atwo-level maximum difference.$\gamma_{l} = {\frac{l}{n}{\sum\limits_{k = 1}^{n}\quad {\xi_{l}(k)}}}$

If all of the γ₁ are not less than R, it means that each of theprogression satisfies the associated matching conditions.

What is claimed is:
 1. A method of detecting fire by smoke-emissionanalysis, comprising the steps of: training across a monitored area tobe protected against fire from one side a plurality of discrete infraredbeams capable of being intercepted by smoke particles emitted upondevelopment of a fire condition; detecting the discrete infrared beamson another side of the monitored area and generating video signals inresponse to detecting, the generated video signals representingattenuation of the discrete infrared beams by smoke particles;processing the video signals to determine at least a possibility of afire condition in the monitored area; enabling an alarm in response todetermining the fire condition if: upon comparing each of the processedvideo signals to an alarm threshold, the processed video signal exceedsthe alarm threshold, upon sequentially comparing each of the processedvideo signals to the alarm threshold and a turning threshold, arespective processed video signal exceeds the turning threshold, or upondetermining that all of the processed video signals exceed the turningthreshold.
 2. The method according to claim 1, wherein the processing isperformed by a computer employing a method selected from the groupconsisting of template matching, tendency analysis, correlation analysisand a combination of these.
 3. The method according to claims 1, furthercomprising the steps of transferring the generated video signals to avideo switcher, and sequentially sending the transferred video signalsone by one in a polling manner to a processor operative to determine thepossibility of the fire condition.
 4. A system for detecting fire bysmoke-emission analysis, comprising: a plurality of infrared radiationarrays mounted in an area to be protected against fire and operative togenerate discrete infrared light beams passing across the area and beinginterceptable by smoke particles emitted upon development of a firecondition; a plurality of detectors mounted in the area at a distancefrom the infrared radiation array and each operative to detect arespective discrete infrared beam and to generate a respective videosignal in response to detecting, the generated video signalsrepresenting attenuation of the discrete infrared beams by smokeparticles; a computer operative to process the video signals todetermine at least a possibility of a fire condition in the area and togenerate an alarm in response to the processing of the video signals inresponse to determining the fire condition in: a first fire recognitionmode, wherein each of the processed signals is compared to an alarmthreshold and enables the alarm upon exceeding the alarm threshold, asecond fire recognition mode, wherein each processed signal issequentially compared to the alarm threshold and a turning threshold todetermine tendency corresponding to the fire condition in the monitoredarea, the processor enabling the alarm only if a respective processedsignal exceeds the turning threshold, and a third fire recognition mode,wherein the alarm is enabled if all of the processed signals exceed theturning threshold.
 5. The system according to claim 4, wherein thedetectors include infrared cameras.
 6. The system according to claim 5,further comprising a video switcher operative to sequentially receivethe generated video signals from the infrared cameras and tosequentially transfer the received generated video signals to thecomputer.
 7. A system for detecting fire by smoke-emission analysis,comprising: a plurality of radiation arrays mounted in an area to beprotected against fire and operative to generate a plurality of discretelight beams passing across the area and being interceptable by smokeparticles emitted upon development of a fire condition; a plurality ofdetectors mounted in the area at a distance from the infrared radiationarrays and each operative to detect a respective discrete light beam andto generate a respective video signal in response to detecting of thelight beam, the generated video signals representing attenuation of thediscrete light beams by smoke particles, each light beam beingcharacterized by a respective intensity reduced upon penetration throughsmoke articles in accordance with the following formula I _(λ) =I_(λ0)exp(−KL), wherein I_(λ) is the detected light bam, I_(λ0) is theintensity of the radiated light beam, L is the average run length of thelight beam, and K is the extinction coefficient and is a function of thediameter of the smoke particles and their density; a processor operativeto process the video signals to determine at least a possibility of afire condition in the space and to generate an alarm in response to theprocessing of the video signals in response to determining the firecondition.
 8. The system according to claim 7, further comprising avideo switcher operative to sequentially receive the detected videosignals and to sequentially send the received video signals to theprocessor.
 9. A system for detecting fire by smoke emission analysis,comprising: a plurality of radiation arrays mounted in an area to beprotected against fire and operative to generate a plurality of discretelight beams passing across the area and being interceptable by smokeparticles emitted upon development of a fire condition; a plurality ofdetectors mounted in the area at a distance from the infrared radiationarrays and each operative to detect a respective discrete light beam andto generate a respective video signal in response to detecting, thegenerated video signals representing attenuation of the discrete lightbeams by smoke particles; a processor operative to process the videosignals to determine at least a possibility of a fire condition in thespace and to generate an alarm in response to the processing of thevideo signals in response to determining the fire condition, theprocessor being a computer operable in a first fire recognition mode,wherein each of the processed signals is compared to an alarm thresholdand enables the alarm upon exceeding the alarm threshold; a second firerecognition mode, wherein each processed signal is sequentially comparedto the alarm threshold and a turning threshold to determine tendencycorresponding to the fire condition in the monitored area, the processorenabling the alarm only if a respective processed signal exceeds theturning threshold; and a third fire recognition mode, wherein the alarmis enabled if all of the processed signals exceed the turning threshold.